Computational methods for ubiquitination site prediction using physicochemical properties of protein sequences

  • Cai B
  • Jiang X
  • 16

    Readers

    Mendeley users who have this article in their library.
  • 0

    Citations

    Citations of this article.

Abstract

Ubiquitination is a very important process in protein post-translational modification, which has been widely investigated by biology scientists and researchers. Different experimental and computational methods have been developed to identify the ubiquitination sites in protein sequences. This paper aims at exploring computational machine learning methods for the prediction of ubiquitination sites using the physicochemical properties (PCPs) of amino acids in the protein sequences.

Author-supplied keywords

  • Amino Acid (AA)
  • Bayesian Network (BN)
  • Least Absolute Shrinkage and Selection Operator (LASSO)
  • Logistic Regression (LR)
  • Machine learning
  • Physicochemical property (PCP)
  • Prediction
  • Protein sequence
  • Support Vector Machine (SVM)
  • Ubiquitination
  • Ubiquitination Site Prediction

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Binghuang Cai

  • Xia Jiang

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free